307 research outputs found
Antiangiogenic Effects and Therapeutic Targets of Azadirachta indica Leaf Extract in Endothelial Cells
Azadirachta indica (common name: neem) leaves have been found to possess immunomodulatory, anti-inflammatory and anti-carcinogenic properties. The present study evaluates anti-angiogenic potential of ethanol extract of neem leaves (EENL) in human umbilical vein endothelial cells (HUVECs). Treatment of HUVECs with EENL inhibited VEGF induced angiogenic response in vitro and in vivo. The in vitro proliferation, invasion and migration of HUVECs were suppressed with EENL. Nuclear fragmentation and abnormally small mitochondria with dilated cristae were observed in EENL treated HUVECs by transmission electron microscopy. Genome-wide mRNA expression profiling after treatment with EENL revealed differentially regulated genes. Expression changes of the genes were validated by quantitative real-time polymerase chain reaction. Additionally, increase in the expression of HMOX1, ATF3 and EGR1 proteins were determined by immunoblotting. Analysis of the compounds in the EENL by mass spectrometry suggests the presence of nimbolide, 2′,3′-dehydrosalannol, 6-desacetyl nimbinene and nimolinone. We further confirmed antiproliferative activity of nimbolide and 2′,3′-dehydrosalannol in HUVECs. Our results suggest that EENL by regulating the genes involved in cellular development and cell death functions could control cell proliferation, attenuate the stimulatory effects of VEGF and exert antiangiogenic effects. EENL treatment could have a potential therapeutic role during cancer progression
Adaptive response and enlargement of dynamic range
Many membrane channels and receptors exhibit adaptive, or desensitized,
response to a strong sustained input stimulus, often supported by protein
activity-dependent inactivation. Adaptive response is thought to be related to
various cellular functions such as homeostasis and enlargement of dynamic range
by background compensation. Here we study the quantitative relation between
adaptive response and background compensation within a modeling framework. We
show that any particular type of adaptive response is neither sufficient nor
necessary for adaptive enlargement of dynamic range. In particular a precise
adaptive response, where system activity is maintained at a constant level at
steady state, does not ensure a large dynamic range neither in input signal nor
in system output. A general mechanism for input dynamic range enlargement can
come about from the activity-dependent modulation of protein responsiveness by
multiple biochemical modification, regardless of the type of adaptive response
it induces. Therefore hierarchical biochemical processes such as methylation
and phosphorylation are natural candidates to induce this property in signaling
systems.Comment: Corrected typos, minor text revision
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Best practices to maximize the use and reuse of quantitative and systems pharmacology models: recommendations from the United Kingdom quantitative and systems pharmacology network
The lack of standardization in the way that quantitative and systems pharmacology (QSP) models are developed, tested, and documented hinders their reproducibility, reusability, and expansion or reduction to alternative contexts. This in turn undermines the potential impact of QSP in academic, industrial, and regulatory frameworks. This article presents a minimum set of recommendations from the UK Quantitative and Systems Pharmacology Network (UK QSP Network) to guide QSP practitioners seeking to maximize their impact, and stakeholders considering the use of QSP models in their environment
Mathematical description of bacterial traveling pulses
The Keller-Segel system has been widely proposed as a model for bacterial
waves driven by chemotactic processes. Current experiments on {\em E. coli}
have shown precise structure of traveling pulses. We present here an
alternative mathematical description of traveling pulses at a macroscopic
scale. This modeling task is complemented with numerical simulations in
accordance with the experimental observations. Our model is derived from an
accurate kinetic description of the mesoscopic run-and-tumble process performed
by bacteria. This model can account for recent experimental observations with
{\em E. coli}. Qualitative agreements include the asymmetry of the pulse and
transition in the collective behaviour (clustered motion versus dispersion). In
addition we can capture quantitatively the main characteristics of the pulse
such as the speed and the relative size of tails. This work opens several
experimental and theoretical perspectives. Coefficients at the macroscopic
level are derived from considerations at the cellular scale. For instance the
stiffness of the signal integration process turns out to have a strong effect
on collective motion. Furthermore the bottom-up scaling allows to perform
preliminary mathematical analysis and write efficient numerical schemes. This
model is intended as a predictive tool for the investigation of bacterial
collective motion
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Overview of mathematical approaches used to model bacterial chemotaxis I: the single cell
Mathematical modeling of bacterial chemotaxis systems has been influential and insightful in helping to understand experimental observations. We provide here a comprehensive overview of the range of mathematical approaches used for modeling, within a single bacterium, chemotactic processes caused by changes to external gradients in its environment. Specific areas of the bacterial system which have been studied and modeled are discussed in detail, including the modeling of adaptation in response to attractant gradients, the intracellular phosphorylation cascade, membrane receptor clustering, and spatial modeling of intracellular protein signal transduction. The importance of producing robust models that address adaptation, gain, and sensitivity are also discussed. This review highlights that while mathematical modeling has aided in understanding bacterial chemotaxis on the individual cell scale and guiding experimental design, no single model succeeds in robustly describing all of the basic elements of the cell. We conclude by discussing the importance of this and the future of modeling in this area
Evaluation of Arctic warming in mid-Pliocene climate simulations
Palaeoclimate simulations improve our understanding of the climate, inform us about the performance of climate models in a different climate scenario, and help to identify robust features of the climate system. Here, we analyse Arctic warming in an ensemble of 16 simulations of the mid-Pliocene Warm Period (mPWP), derived from the Pliocene Model Intercomparison Project Phase 2 (PlioMIP2).
The PlioMIP2 ensemble simulates Arctic (60–90∘ N) annual mean surface air temperature (SAT) increases of 3.7 to 11.6 ∘C compared to the pre-industrial period, with a multi-model mean (MMM) increase of 7.2 ∘C. The Arctic warming amplification ratio relative to global SAT anomalies in the ensemble ranges from 1.8 to 3.1 (MMM is 2.3). Sea ice extent anomalies range from −3.0 to −10.4×10^{6} km^{2}, with a MMM anomaly of −5.6×10^{6} km^{2}, which constitutes a decrease of 53 % compared to the pre-industrial period. The majority (11 out of 16) of models simulate summer sea-ice-free conditions (≤1×10^{6} km^{2}) in their mPWP simulation. The ensemble tends to underestimate SAT in the Arctic when compared to available reconstructions, although the degree of underestimation varies strongly between the simulations. The simulations with the highest Arctic SAT anomalies tend to match the proxy dataset in its current form better. The ensemble shows some agreement with reconstructions of sea ice, particularly with regard to seasonal sea ice. Large uncertainties limit the confidence that can be placed in the findings and the compatibility of the different proxy datasets. We show that while reducing uncertainties in the reconstructions could decrease the SAT data–model discord substantially, further improvements are likely to be found in enhanced boundary conditions or model physics. Lastly, we compare the Arctic warming in the mPWP to projections of future Arctic warming and find that the PlioMIP2 ensemble simulates greater Arctic amplification than CMIP5 future climate simulations and an increase instead of a decrease in Atlantic Meridional Overturning Circulation (AMOC) strength compared to pre-industrial period. The results highlight the importance of slow feedbacks in equilibrium climate simulations, and that caution must be taken when using simulations of the mPWP as an analogue for future climate change
A return to large-scale features of Pliocene climate: the Pliocene Model Intercomparison Project Phase 2
The Pliocene epoch has great potential to improve our understanding of the long-term climatic and environmental consequences of an atmospheric CO2 concentration near ~ 400 parts per million by volume. Here we present the large-scale features of Pliocene climate as simulated by a new ensemble of climate models of varying complexity and spatial resolution and based on new reconstructions of boundary conditions (the Pliocene Model Intercomparison Project Phase 2; PlioMIP2). As a global annual average, modelled surface air temperatures increase by between 1.4 and 4.7 °C relative to pre-industrial with a multi-model mean value of 2.8 °C. Annual mean total precipitation rates increase by 6 % (range: 2 %–13 %). On average, surface air temperature (SAT) increases are 1.3 °C greater over the land than over the oceans, and there is a clear pattern of polar amplification with warming polewards of 60° N and 60° S exceeding the global mean warming by a factor of 2.4. In the Atlantic and Pacific Oceans, meridional temperature gradients are reduced, while tropical zonal gradients remain largely unchanged. Although there are some modelling constraints, there is a statistically significant relationship between a model's climate response associated with a doubling in CO2 (Equilibrium Climate Sensitivity; ECS) and its simulated Pliocene surface temperature response. The mean ensemble earth system response to doubling of CO2 (including ice sheet feedbacks) is approximately 50 % greater than ECS, consistent with results from the PlioMIP1 ensemble. Proxy-derived estimates of Pliocene sea-surface temperatures are used to assess model estimates of ECS and indicate a range in ECS from 2.5 to 4.3 °C. This result is in general accord with the range in ECS presented by previous IPCC Assessment Reports
Nonperturbative renormalization group approach to frustrated magnets
This article is devoted to the study of the critical properties of classical
XY and Heisenberg frustrated magnets in three dimensions. We first analyze the
experimental and numerical situations. We show that the unusual behaviors
encountered in these systems, typically nonuniversal scaling, are hardly
compatible with the hypothesis of a second order phase transition. We then
review the various perturbative and early nonperturbative approaches used to
investigate these systems. We argue that none of them provides a completely
satisfactory description of the three-dimensional critical behavior. We then
recall the principles of the nonperturbative approach - the effective average
action method - that we have used to investigate the physics of frustrated
magnets. First, we recall the treatment of the unfrustrated - O(N) - case with
this method. This allows to introduce its technical aspects. Then, we show how
this method unables to clarify most of the problems encountered in the previous
theoretical descriptions of frustrated magnets. Firstly, we get an explanation
of the long-standing mismatch between different perturbative approaches which
consists in a nonperturbative mechanism of annihilation of fixed points between
two and three dimensions. Secondly, we get a coherent picture of the physics of
frustrated magnets in qualitative and (semi-) quantitative agreement with the
numerical and experimental results. The central feature that emerges from our
approach is the existence of scaling behaviors without fixed or pseudo-fixed
point and that relies on a slowing-down of the renormalization group flow in a
whole region in the coupling constants space. This phenomenon allows to explain
the occurence of generic weak first order behaviors and to understand the
absence of universality in the critical behavior of frustrated magnets.Comment: 58 pages, 15 PS figure
The Role of Genomics in the Identification, Prediction, and Prevention of Biological Threats
In all likelihood, it is only a matter of time before our public health system will face a major biological threat, whether intentionally dispersed or originating from a known or newly emerging infectious disease. It is necessary not only to increase our reactive “biodefense,” but also to be proactive and increase our preparedness. To achieve this goal, it is essential that the scientific and public health communities fully embrace the genomic revolution, and that novel bioinformatic and computing tools necessary to make great strides in our understanding of these novel and emerging threats be developed. Genomics has graduated from a specialized field of science to a research tool that soon will be routine in research laboratories and clinical settings. Because the technology is becoming more affordable, genomics can and should be used proactively to build our preparedness and responsiveness to biological threats. All pieces, including major continued funding, advances in next-generation sequencing technologies, bioinformatics infrastructures, and open access to data and metadata, are being set in place for genomics to play a central role in our public health system
The Pliocene Model Intercomparison Project Phase 2: large-scale climate features and climate sensitivity
The Pliocene epoch has great potential to improve our understanding of the long-term climatic and environmental consequences of an atmospheric CO2 concentration near ∼400 parts per million by volume. Here we present the large-scale features of Pliocene climate as simulated by a new ensemble of climate models of varying complexity and spatial resolution based on new reconstructions of boundary conditions (the Pliocene Model Intercomparison Project Phase 2; PlioMIP2). As a global annual average, modelled surface air temperatures increase by between 1.7 and 5.2 ∘C relative to the pre-industrial era with a multi-model mean value of 3.2 ∘C. Annual mean total precipitation rates increase by 7 % (range: 2 %–13 %). On average, surface air temperature (SAT) increases by 4.3 ∘C over land and 2.8 ∘C over the oceans. There is a clear pattern of polar amplification with warming polewards of 60∘ N and 60∘ S exceeding the global mean warming by a factor of 2.3. In the Atlantic and Pacific oceans, meridional temperature gradients are reduced, while tropical zonal gradients remain largely unchanged. There is a statistically significant relationship between a model's climate response associated with a doubling in CO2 (equilibrium climate sensitivity; ECS) and its simulated Pliocene surface temperature response. The mean ensemble Earth system response to a doubling of CO2 (including ice sheet feedbacks) is 67 % greater than ECS; this is larger than the increase of 47 % obtained from the PlioMIP1 ensemble. Proxy-derived estimates of Pliocene sea surface temperatures are used to assess model estimates of ECS and give an ECS range of 2.6–4.8 ∘C. This result is in general accord with the ECS range presented by previous Intergovernmental Panel on Climate Change (IPCC) Assessment Reports
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